A Nomogram for Predicting Cancer-Specific Survival of TNM 8th Edition Stage I Non-small-cell Lung Cancer

the AME Thoracic Surgery Collaborative Group

Research output: Contribution to journalArticle

2 Citations (Scopus)

Abstract

Background: Models for predicting the survival outcomes of stage I non-small-cell lung cancer (NSCLC) defined by the newly released 8th edition TNM staging system are scarce. This study aimed to develop a nomogram for predicting the cancer-specific survival (CSS) of these patients and identifying individuals with a higher risk for CSS. Methods: A total of 30,475 NSCLC cases were extracted from the Surveillance, Epidemiology, and End Results (SEER) database. We identified and integrated the risk factors to build a nomogram. The model was subjected to bootstrap internal validation with the SEER database, and external validation with a multicenter cohort of 1133 patients from China. The difference in the impact of adjuvant chemotherapy on model-defined high- and low-risk patients was examined using the National Cancer Database (NCDB). Results: Eight independent prognostic factors were identified and integrated into the model. The calibration curves showed good agreement. The concordance index (C-index) of the nomogram was higher than that of the staging system (IA1, IA2, IA3, and IB) (internal validation set 0.63 vs. 0.56; external validation set 0.66 vs. 0.55; both p < 0.01). Specifically, 21.7% of stage IB patients (7.5% of all stage I) were categorized into the high-risk group (score > 30). There was a significant interaction effect between the adjuvant chemotherapy and risk groups in the NCDB cohort (p = 0.003). Conclusions: We established a practical nomogram to predict CSS for 8th edition stage I NSCLC. A prospective study is warranted to determine its role in identifying adjuvant chemotherapy candidates.

Original languageEnglish
JournalAnnals of Surgical Oncology
DOIs
Publication statusPublished - Jan 1 2019

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Nomograms
Non-Small Cell Lung Carcinoma
Adjuvant Chemotherapy
Survival
Databases
Neoplasms
Epidemiology
Neoplasm Staging
Calibration
China
Prospective Studies

ASJC Scopus subject areas

  • Surgery
  • Oncology

Cite this

A Nomogram for Predicting Cancer-Specific Survival of TNM 8th Edition Stage I Non-small-cell Lung Cancer. / the AME Thoracic Surgery Collaborative Group.

In: Annals of Surgical Oncology, 01.01.2019.

Research output: Contribution to journalArticle

@article{d317035ffcda4695ad85fb3a632b49c0,
title = "A Nomogram for Predicting Cancer-Specific Survival of TNM 8th Edition Stage I Non-small-cell Lung Cancer",
abstract = "Background: Models for predicting the survival outcomes of stage I non-small-cell lung cancer (NSCLC) defined by the newly released 8th edition TNM staging system are scarce. This study aimed to develop a nomogram for predicting the cancer-specific survival (CSS) of these patients and identifying individuals with a higher risk for CSS. Methods: A total of 30,475 NSCLC cases were extracted from the Surveillance, Epidemiology, and End Results (SEER) database. We identified and integrated the risk factors to build a nomogram. The model was subjected to bootstrap internal validation with the SEER database, and external validation with a multicenter cohort of 1133 patients from China. The difference in the impact of adjuvant chemotherapy on model-defined high- and low-risk patients was examined using the National Cancer Database (NCDB). Results: Eight independent prognostic factors were identified and integrated into the model. The calibration curves showed good agreement. The concordance index (C-index) of the nomogram was higher than that of the staging system (IA1, IA2, IA3, and IB) (internal validation set 0.63 vs. 0.56; external validation set 0.66 vs. 0.55; both p < 0.01). Specifically, 21.7{\%} of stage IB patients (7.5{\%} of all stage I) were categorized into the high-risk group (score > 30). There was a significant interaction effect between the adjuvant chemotherapy and risk groups in the NCDB cohort (p = 0.003). Conclusions: We established a practical nomogram to predict CSS for 8th edition stage I NSCLC. A prospective study is warranted to determine its role in identifying adjuvant chemotherapy candidates.",
author = "{the AME Thoracic Surgery Collaborative Group} and Yuan Zeng and Nicholas Mayne and Yang, {Chi Fu Jeffrey} and D’Amico, {Thomas A.} and Ng, {Calvin S.H.} and Liu, {Chia chuan} and Petersen, {Ren{\'e} Horsleben} and Gaetano Rocco and Alessandro Brunelli and Jun Liu and Yang Liu and Weizhe Huang and Jiaxi He and Wei Wang and Long Jiang and Fei Cui and Wenjun Wang and Wenhua Liang and Jianxing He",
year = "2019",
month = "1",
day = "1",
doi = "10.1245/s10434-019-07318-7",
language = "English",
journal = "Annals of Surgical Oncology",
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T1 - A Nomogram for Predicting Cancer-Specific Survival of TNM 8th Edition Stage I Non-small-cell Lung Cancer

AU - the AME Thoracic Surgery Collaborative Group

AU - Zeng, Yuan

AU - Mayne, Nicholas

AU - Yang, Chi Fu Jeffrey

AU - D’Amico, Thomas A.

AU - Ng, Calvin S.H.

AU - Liu, Chia chuan

AU - Petersen, René Horsleben

AU - Rocco, Gaetano

AU - Brunelli, Alessandro

AU - Liu, Jun

AU - Liu, Yang

AU - Huang, Weizhe

AU - He, Jiaxi

AU - Wang, Wei

AU - Jiang, Long

AU - Cui, Fei

AU - Wang, Wenjun

AU - Liang, Wenhua

AU - He, Jianxing

PY - 2019/1/1

Y1 - 2019/1/1

N2 - Background: Models for predicting the survival outcomes of stage I non-small-cell lung cancer (NSCLC) defined by the newly released 8th edition TNM staging system are scarce. This study aimed to develop a nomogram for predicting the cancer-specific survival (CSS) of these patients and identifying individuals with a higher risk for CSS. Methods: A total of 30,475 NSCLC cases were extracted from the Surveillance, Epidemiology, and End Results (SEER) database. We identified and integrated the risk factors to build a nomogram. The model was subjected to bootstrap internal validation with the SEER database, and external validation with a multicenter cohort of 1133 patients from China. The difference in the impact of adjuvant chemotherapy on model-defined high- and low-risk patients was examined using the National Cancer Database (NCDB). Results: Eight independent prognostic factors were identified and integrated into the model. The calibration curves showed good agreement. The concordance index (C-index) of the nomogram was higher than that of the staging system (IA1, IA2, IA3, and IB) (internal validation set 0.63 vs. 0.56; external validation set 0.66 vs. 0.55; both p < 0.01). Specifically, 21.7% of stage IB patients (7.5% of all stage I) were categorized into the high-risk group (score > 30). There was a significant interaction effect between the adjuvant chemotherapy and risk groups in the NCDB cohort (p = 0.003). Conclusions: We established a practical nomogram to predict CSS for 8th edition stage I NSCLC. A prospective study is warranted to determine its role in identifying adjuvant chemotherapy candidates.

AB - Background: Models for predicting the survival outcomes of stage I non-small-cell lung cancer (NSCLC) defined by the newly released 8th edition TNM staging system are scarce. This study aimed to develop a nomogram for predicting the cancer-specific survival (CSS) of these patients and identifying individuals with a higher risk for CSS. Methods: A total of 30,475 NSCLC cases were extracted from the Surveillance, Epidemiology, and End Results (SEER) database. We identified and integrated the risk factors to build a nomogram. The model was subjected to bootstrap internal validation with the SEER database, and external validation with a multicenter cohort of 1133 patients from China. The difference in the impact of adjuvant chemotherapy on model-defined high- and low-risk patients was examined using the National Cancer Database (NCDB). Results: Eight independent prognostic factors were identified and integrated into the model. The calibration curves showed good agreement. The concordance index (C-index) of the nomogram was higher than that of the staging system (IA1, IA2, IA3, and IB) (internal validation set 0.63 vs. 0.56; external validation set 0.66 vs. 0.55; both p < 0.01). Specifically, 21.7% of stage IB patients (7.5% of all stage I) were categorized into the high-risk group (score > 30). There was a significant interaction effect between the adjuvant chemotherapy and risk groups in the NCDB cohort (p = 0.003). Conclusions: We established a practical nomogram to predict CSS for 8th edition stage I NSCLC. A prospective study is warranted to determine its role in identifying adjuvant chemotherapy candidates.

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DO - 10.1245/s10434-019-07318-7

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